Show simple item record

dc.contributor.authorVon Schwerin, Erik
dc.date.accessioned2017-06-08T06:32:30Z
dc.date.available2017-06-08T06:32:30Z
dc.date.issued2016-01-08
dc.identifier.urihttp://hdl.handle.net/10754/624864
dc.description.abstractI will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.
dc.titleOptimal mesh hierarchies in Multilevel Monte Carlo methods
dc.typePresentation
dc.conference.dateJanuary 5-10, 2016
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2016)
dc.conference.locationKAUST
dc.contributor.institutionUniversity of Delaware
refterms.dateFOA2018-06-13T14:49:46Z


Files in this item

This item appears in the following Collection(s)

Show simple item record